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Record W4299558177 · doi:10.5281/zenodo.4585711

Enquête sur les initiatives canadiennes et internationales en matière de la gestion des données

2008· report· fr· W4299558177 on OpenAlexaffabout
Diego Argáez, Kathleen Shearer

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2008
Typereport
Languagefr
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsCanadian Association of Research Libraries
Fundersnot available
KeywordsPolitical science

Abstract

Le présent rapport vise à donner une vue d’ensemble des types d’activités de gestion des données qui sont entreprises au Canada et à l’étranger. Nous présentons les diverses options offertes aux bibliothèques et nous préparons le terrain pour une enquête plus approfondie par le groupe de travail sur les rôles possibles des bibliothèques.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this metaresearch. It is in the settled core of the field.

stratum: french · design weight: 1554.47 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8T2
genre: empirical
about Canada: yes
confidence: medium

Research library association survey of Canadian and international research data management initiatives and the roles open to libraries; LIS and research data infrastructure, with the Canadian landscape as a substantive object.

GPT-5.6 (high)T2
genre: conceptual
about Canada: yes
confidence: high

This report maps Canadian and international research data management initiatives and library roles, making research infrastructure its object.

Grok 4.5T2
genre: policy
about Canada: yes
confidence: high

Landscape report of Canadian and international research data management initiatives and library roles; research infrastructure/LIS with Canada as substantive object.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0160.037
Science and technology studies0.0110.005
Scholarly communication0.0200.009
Open science0.0020.008
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0200.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.280
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2008
Admission routes2
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicSemantic Web and OntologiesFrench-language works237,207